Pier-Jean Malandrino ba54427445 feat(#180 ): feature-flag ingestion pipeline and add brainless one-liner Quick Start

- Conditionally mount ingestion router only when OpenSearch + embedding are configured
- Add `ingestionAvailable` field to /api/health response
- Add `ingestion` feature flag to frontend (hides Search nav, Ingest button,
  OpenSearch badge, indexed badges/filters when disabled)
- Skip ingestion polling when flag is off
- Make OpenSearch + embedding optional in docker-compose via profiles
- Add docker-compose.ingestion.yml override for full-stack ingestion
- Set BATCH_PAGE_SIZE=5 default in Docker local image
- Lead Quick Start with one-liner docker run command
- Document ingestion as opt-in with dedicated section
- Add BATCH_PAGE_SIZE, MAX_FILE_SIZE_MB, MAX_PAGE_COUNT, RATE_LIMIT_RPM to config tables
- Update test counts (380 backend, 159 frontend)
- Date CHANGELOG 0.4.0, bump frontend version to 0.4.0
- Sync CONTRIBUTING.md with E2E Karate test sections

Closes #180

2026-04-13 11:18:56 +02:00

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Docling Studio

A visual document analysis studio powered by Docling.

Upload a PDF, configure the extraction pipeline, and visualize the results — text, tables, images, formulas, bounding boxes — all from your browser.

{ width="600" }

Features

PDF viewer with page navigation, bounding box overlay, and resizable results panel
Configurable Docling pipeline — OCR, table extraction, code/formula enrichment, picture classification & description, image generation
Bounding box visualization — color-coded element overlay directly on the PDF
Chunking — split extracted content into semantic chunks (hierarchical, hybrid, or page-based) with configurable token limits
Markdown & HTML export of extracted content
Document management — upload, list, delete
Analysis history — re-visit and open past analyses
Feature flags — capabilities adapt to the conversion engine (local vs remote)
Upload limits — configurable max file size (MAX_FILE_SIZE_MB) and max page count (MAX_PAGE_COUNT) per document
Rate limiting — configurable requests per minute per IP (RATE_LIMIT_RPM)
Deployment modes — self-hosted (default) or HuggingFace Spaces (with disclaimer banner)
Health endpoint — /api/health reports engine type, deployment mode, and database status
Dark / Light theme and FR / EN localization

Tech Stack

Layer	Stack
Frontend	Vue 3, TypeScript, Vite, Pinia
Backend	FastAPI, Docling 2.x, SQLite (aiosqlite)
CI	GitHub Actions (lint, type-check, test, build)
Infra	Docker Compose + Nginx

Quick Start

# Docker (fastest)
docker run -p 3000:3000 ghcr.io/scub-france/docling-studio:latest-local

Open http://localhost:3000 and upload a PDF.

!!! note The first analysis takes longer as Docling downloads its ML models (~400 MB). Subsequent runs are fast.

See Getting Started for local development setup.

License

MIT — Pier-Jean Malandrino

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